Within the field of imaging, many scenarios involve the generation of a composite image using a set of monochromatic images, such as images captured by respective image sensors respectively positioned behind red, green, and blue color filters of a Bayer filter array. In many such scenarios, the pixels of respective input monochromatic images may represent a mosaic, and each (achromatic) pixel of a composite image may be generated through a “de-mosaicing” calculation based on the set of corresponding monochromatic pixels in approximately the same position of the monochromatic images. However, many such techniques may result in chromatic inaccuracies or artifacts, as the reconstruction of the captured color of each composite pixel from the mosaic of captured monochromatic images may not precisely and accurately reflect the relevant portion of the visible spectrum.
In addition, many such scenarios also involve an input achromatic image captured through a different image sensor, such as a panchromatic image captured by an unfiltered image sensor that captures a large range of the achromatic spectrum, or an infrared or near-infrared image captured by an image sensor positioned behind an infrared-passing or near-infrared-passing filter. As a first example, the inclusion of achromatic pixels of the achromatic image with the corresponding monochromatic pixels may facilitate accurate per-pixel color reconstruction. For example, the luminance of a panchromatic pixel may be compared with the composite luminance of the respective monochromatic pixels, and a proportional scaling may be applied to adjust the intensity of the monochromatic pixels to match the luminance of the panchromatic pixel. As a second example, the monochromatic image may be captured with a higher resolution than the monochromatic images. A pan-sharpening technique may be utilized to combine the color data from the lower-resolution monochromatic images and the higher resolution of the monochromatic image to produce a high-resolution, color composite image. As a third example, in some types of imaging, an achromatic image may capture particular types of information that are not fully captured by the monochromatic images. For example, in aerial photography, infrared and near-infrared images may more accurately reflect edge detail of trees and bodies of water than monochromatic images, and the composite image may result in more accurate edge detail for such objects. For these and other reasons, many cameras and image processing techniques may utilize a combination of monochromatic and achromatic images to generate composite images having various advantageous properties.